---
title: "Who cites ALBERT: A Lite — page 2 — 1,861 citing papers"
description: "1,861 papers of the Elamur Research library cite «ALBERT: A Lite BERT for Self-supervised Learning of Language Representations», found…"
canonical: "https://research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/page/2/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/page/2/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [ALBERT: A Lite BERT for Self-supervised Learning…](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/) / [cited by](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/) / page 2

# Who cites «ALBERT: A Lite BERT for Self-supervised Learning of Language Representations»

1,861 papers of our library cite it (of the 149,439 whose bibliographies we read) · 262 with a page here, the most cited first · page 2 of 3 · 101–200 · [← back to «ALBERT: A Lite BERT for Self-supervised Learning of Language Representations»](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/)

[← prev](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/) **2** [3](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/page/3/) [next →](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/page/3/)

101. **[TernaryBERT: Distillation-aware Ultra-low Bit BERT](https://md.research.elamur.ai/free/en/papers/zhang-2020-ternarybert-distillation-aware-ultra-low/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wei Zhang, Lu Hou, Yichun Yin, et al.*2020 · 213 citations*
102. **[Training Question Answering Models From Synthetic Data](https://md.research.elamur.ai/free/en/papers/puri-2020-training-question-answering-models-synthetic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Raul Puri, Ryan Spring, Mohammad Shoeybi, et al.*2020 · 208 citations*
103. **[CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters](https://md.research.elamur.ai/free/en/papers/boukkouri-2020-characterbert-reconciling-elmo-bert-word/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Hicham El Boukkouri, Olivier Ferret, Thomas Lavergne, et al.*2020 · 206 citations*
104. **[Structured Pruning of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2020-structured-pruning-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ziheng Wang, Jeremy Wohlwend, Tao Lei*2020 · 202 citations*
105. **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations*
106. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining arXiv:2102.08473**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 198 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/)
107. **[Q²: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering](https://md.research.elamur.ai/free/en/papers/honovich-2021-q-2-evaluating-factual-consistency/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Or Honovich, Leshem Choshen, Roee Aharoni, et al.*2021 · 196 citations*
108. **[What Can We Learn from Collective Human Opinions on Natural Language Inference Data?](https://md.research.elamur.ai/free/en/papers/nie-2020-what-can-we-learn-collective/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yixin Nie, Xiang Zhou, Mohit Bansal*2020 · 196 citations*
109. **[Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts](https://md.research.elamur.ai/free/en/papers/guo-2022-auto-debias-debiasing-masked-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yue Guo, Yi Yang, Ahmed Abbasi*2022 · 191 citations*
110. **[SemEval-2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER)](https://md.research.elamur.ai/free/en/papers/malmasi-2022-semeval-2022-task-11-multilingual/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Shervin Malmasi, Anjie Fang, Besnik Fetahu, et al.*2022 · 190 citations*
111. **[Compressing Large-Scale Transformer-Based Models: A Case Study on BERT](https://md.research.elamur.ai/free/en/papers/ganesh-2021-compressing-large-scale-transformer-based/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Prakhar Ganesh, Yao Chen, Xin Lou, et al.*2021 · 190 citations*
112. **[GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer](https://md.research.elamur.ai/free/en/papers/zaratiana-2024-gliner-generalist-model-named-entity/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Urchade Zaratiana, Nadi Tomeh, Pierre Holat, et al.*2024 · 189 citations*
113. **[Packed Levitated Marker for Entity and Relation Extraction](https://md.research.elamur.ai/free/en/papers/ye-2022-packed-levitated-marker-entity-relation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deming Ye, Yankai Lin, Peng Li, et al.*2022 · 189 citations*
114. **[Gradient-based Adversarial Attacks against Text Transformers](https://md.research.elamur.ai/free/en/papers/guo-2021-gradient-based-adversarial-attacks-against/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chuan Guo, Alexandre Sablayrolles, Hervé Jégou, et al.*2021 · 189 citations*
115. **[Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer](https://md.research.elamur.ai/free/en/papers/qi-2021-mind-style-text-adversarial-backdoor/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fanchao Qi, Yangyi Chen, Xurui Zhang, et al.*2021 · 189 citations*
116. **[NILE : Natural Language Inference with Faithful Natural Language Explanations](https://md.research.elamur.ai/free/en/papers/kumar-2020-nile-natural-language-inference-faithful/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sawan Kumar, Partha Talukdar*2020 · 184 citations*
117. **[Debiasing Pre-trained Contextualised Embeddings](https://md.research.elamur.ai/free/en/papers/kaneko-2021-debiasing-pre-trained-contextualised-embeddings/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Masahiro Kaneko, Danushka Bollegala*2021 · 175 citations*
118. **[Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages](https://md.research.elamur.ai/free/en/papers/doddapaneni-2023-leaving-no-indic-language-behind/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sumanth Doddapaneni, Rahul Aralikatte, Gowtham Ramesh, et al.*2023 · 174 citations*
119. **[KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation](https://md.research.elamur.ai/free/en/papers/chen-2020-kgpt-knowledge-grounded-pre-training/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhu Chen, Yu Su, Xifeng Yan, et al.*2020 · 174 citations*
120. **[The Troubling Emergence of Hallucination in Large Language Models - An Extensive Definition, Quantification, and Prescriptive Remediations](https://md.research.elamur.ai/free/en/papers/rawte-2023-troubling-emergence-hallucination-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, et al.*2023 · 171 citations*
121. [**GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher arXiv:2308.06463**Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-gpt-4-too-smart-safe/)
122. **[Label Verbalization and Entailment for Effective Zero and Few-Shot Relation Extraction](https://md.research.elamur.ai/free/en/papers/sainz-2021-label-verbalization-entailment-effective-zero/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Oscar Sainz, Oier Lopez de Lacalle, Gorka Labaka, et al.*2021 · 167 citations*
123. **[BinaryBERT: Pushing the Limit of BERT Quantization](https://md.research.elamur.ai/free/en/papers/bai-2021-binarybert-pushing-limit-bert-quantization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoli Bai, Wei Zhang, Lu Hou, et al.*2021 · 166 citations*
124. **[ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/xiao-2020-ernie-gen-enhanced-multi/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Dongling Xiao, Han Zhang, Yukun Li, et al.*2020 · 163 citations*
125. [**CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims arXiv:2012.00614**Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian, et al.*2020 · 158 citations*](https://md.research.elamur.ai/free/en/papers/diggelmann-2020-climate-fever-dataset-verification-real/)
126. **[SemEval-2020 Task 4: Commonsense Validation and Explanation](https://md.research.elamur.ai/free/en/papers/wang-2020-semeval-2020-task-4-commonsense/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Cunxiang Wang, Shuailong Liang, Yili Jin, et al.*2020 · 158 citations*
127. [**Leveraging Large Language Models for Multiple Choice Question Answering arXiv:2210.12353**Joshua Robinson, Christopher Michael Rytting, David Wingate*2022 · 157 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2022-leveraging-large-language-models-multiple/)
128. **[CPM: A Large-scale Generative Chinese Pre-trained Language Model](https://md.research.elamur.ai/free/en/papers/zhang-2020-cpm-large-scale-generative/) [AI Open](https://md.research.elamur.ai/free/en/venues/ai-open/)**Zhengyan Zhang, Xu Han, Hao Zhou, et al.*2020 · 150 citations*
129. **[Out of Order: How important is the sequential order of words in a sentence in Natural Language Understanding tasks?](https://md.research.elamur.ai/free/en/papers/pham-2021-out-order-how-important-is/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Thang Pham, Trung Bui, Long Mai, et al.*2021 · 148 citations*
130. **[Efficient Methods for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.*2023 · 145 citations*
131. **[SemEval 2021 Task 7: HaHackathon, Detecting and Rating Humor and Offense](https://md.research.elamur.ai/free/en/papers/meaney-2021-semeval-2021-task-7-hahackathon/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**J. A. Meaney, Steven Wilson, Luis Chiruzzo, et al.*2021 · 142 citations*
132. [**Rethinking embedding coupling in pre-trained language models arXiv:2010.12821**Hyung Won Chung, Thibault Févry, Henry Tsai, et al.*2020 · 142 citations*](https://md.research.elamur.ai/free/en/papers/chung-2020-rethinking-embedding-coupling-pre-trained/)
133. **[IndicBART: A Pre-trained Model for Indic Natural Language Generation](https://md.research.elamur.ai/free/en/papers/dabre-2022-indicbart-pre-trained-model-indic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Raj Dabre, Himani Shrotriya, Anoop Kunchukuttan, et al.*2022 · 141 citations*
134. **[ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning](https://md.research.elamur.ai/free/en/papers/qin-2021-erica-improving-entity-relation-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yujia Qin, Yankai Lin, Ryuichi Takanobu, et al.*2021 · 139 citations*
135. [**Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches arXiv:1904.01172**Shane Storks, Qiaozi Gao, Joyce Y. Chai*2019 · 135 citations*](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/)
136. **[Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics](https://md.research.elamur.ai/free/en/papers/bhargava-2021-generalization-nli-ways-not-go/) [Workshop on Insights from Negative Results in NLP](https://md.research.elamur.ai/free/en/venues/insights/)**Prajjwal Bhargava, Aleksandr Drozd, Anna Rogers*2021 · 131 citations*
137. **[Improving Factual Consistency of Abstractive Summarization via Question Answering](https://md.research.elamur.ai/free/en/papers/nan-2021-improving-factual-consistency-abstractive-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feng Nan, Cicero Nogueira dos Santos, Henghui Zhu, et al.*2021 · 129 citations*
138. **[Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark](https://md.research.elamur.ai/free/en/papers/niklaus-2021-swiss-judgment-prediction-multilingual-legal/) [Natural Legal Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/nllp/)**Joel Niklaus, Ilias Chalkidis, Matthias Stürmer*2021 · 129 citations*
139. **[The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems](https://md.research.elamur.ai/free/en/papers/ziems-2022-moral-integrity-corpus-benchmark-ethical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Caleb Ziems, Jane A. Yu, Yi-Chia Wang, et al.*2022 · 122 citations*
140. **[I-BERT: Integer-only BERT Quantization](https://md.research.elamur.ai/free/en/papers/kim-2021-i-bert-integer-only-bert/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Sehoon Kim, Amir Gholami, Zhewei Yao, et al.*2021 · 122 citations*
141. **[Logical Fallacy Detection](https://md.research.elamur.ai/free/en/papers/jin-2022-logical-fallacy-detection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, et al.*2022 · 119 citations*
142. **[End-to-End Training of Neural Retrievers for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/sachan-2021-end-end-training-neural-retrievers/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Devendra Sachan, Mostofa Patwary, Mohammad Shoeybi, et al.*2021 · 116 citations*
143. **[Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias](https://md.research.elamur.ai/free/en/papers/bartl-2020-unmasking-contextual-stereotypes-measuring-mitigating/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Marion Bartl, Malvina Nissim, Albert Gatt*2020 · 116 citations*
144. **[WiCE: Real-World Entailment for Claims in Wikipedia](https://md.research.elamur.ai/free/en/papers/kamoi-2023-wice-real-world-entailment-claims/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ryo Kamoi, Tanya Goyal, Juan Diego Rodriguez, et al.*2023 · 113 citations*
145. **[French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English](https://md.research.elamur.ai/free/en/papers/neveol-2022-french-crows-pairs-extending-challenge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aurélie Névéol, Yoann Dupont, Julien Bezançon, et al.*2022 · 107 citations*
146. **[Transformers for Tabular Data Representation: A Survey of Models and Applications](https://md.research.elamur.ai/free/en/papers/badaro-2023-transformers-tabular-data-representation-survey/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Gilbert Badaro, Mohammed Saeed, Paolo Papotti*2023 · 104 citations*
147. **[On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations](https://md.research.elamur.ai/free/en/papers/cao-2022-intrinsic-extrinsic-fairness-evaluation-metrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, et al.*2022 · 100 citations*
148. **[Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation](https://md.research.elamur.ai/free/en/papers/bulian-2022-tomayto-tomahto-beyond-token-level/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jannis Bulian, Christian Buck, Wojciech Gajewski, et al.*2022 · 100 citations*
149. **[True Few-Shot Learning with Prompts–-A Real-World Perspective](https://md.research.elamur.ai/free/en/papers/schick-2022-true-few-shot-learning-prompts/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Timo Schick, Hinrich Schütze*2022 · 96 citations*
150. [**SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning**Roshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, et al.*2021 · 95 citations*](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/)
151. **[A Report on the 2020 Sarcasm Detection Shared Task](https://md.research.elamur.ai/free/en/papers/ghosh-2020-report-2020-sarcasm-detection-shared/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Debanjan Ghosh, Avijit Vajpayee, Smaranda Muresan*2020 · 92 citations*
152. **[Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?](https://md.research.elamur.ai/free/en/papers/tay-2023-scaling-laws-vs-model-architectures/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2023 · 86 citations*
153. **[ORCA: A Challenging Benchmark for Arabic Language Understanding](https://md.research.elamur.ai/free/en/papers/elmadany-2023-orca-challenging-benchmark-arabic-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**AbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed*2023 · 83 citations*
154. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
155. **[Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization](https://md.research.elamur.ai/free/en/papers/laskar-2022-domain-adaptation-pre-trained-transformers/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Md Tahmid Rahman Laskar, Enamul Hoque, Jimmy Xiangji Huang*2022 · 76 citations*
156. **[Structural Persistence in Language Models: Priming as a Window into Abstract Language Representations](https://md.research.elamur.ai/free/en/papers/sinclair-2022-structural-persistence-language-models-priming/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Arabella Sinclair, Jaap Jumelet, Willem Zuidema, et al.*2022 · 74 citations*
157. [**CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark arXiv:2106.08087**Ningyu Zhang, Mosha Chen, Zhen Bi, et al.*2021 · 71 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2021-cblue-chinese-biomedical-language/)
158. **[NormBank: A Knowledge Bank of Situational Social Norms](https://md.research.elamur.ai/free/en/papers/ziems-2023-normbank-knowledge-bank-situational-social/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Caleb Ziems, Jane Dwivedi-Yu, Yi-Chia Wang, et al.*2023 · 69 citations*
159. [**CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese arXiv:2001.04351**Liang Xu, Yu tong, Qianqian Dong, et al.*2020 · 69 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-cluener2020-fine-grained-named/)
160. **[Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints](https://md.research.elamur.ai/free/en/papers/wang-2020-faithful-neural-table-text-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenyi Wang, Xiaoyang Wang, Bang An, et al.*2020 · 67 citations*
161. [**ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2112.12731**Shuohuan Wang, Yu Sun, Yang Xiang, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-ernie-3-0-titan/)
162. [**Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering**Najoung Kim, Ellie Pavlick, Burcu Karagol Ayan, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-which-linguist-invented-lightbulb-presupposition/)
163. [**Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases arXiv:2303.14742**Yunjie Ji, Yong Deng, Yan Gong, et al.*2023 · 62 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-exploring-impact-instruction-data/)
164. [**Building a Bridge: A Method for Image-Text Sarcasm Detection Without Pretraining on Image-Text Data Proceedings of the First International Workshop on Natural Language Processing Beyond Text**Xinyu Wang, Xiaowen Sun, Tan Yang, et al.*2020 · 62 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-building-bridge-method-image-text/)
165. **[A Family of Pretrained Transformer Language Models for Russian](https://md.research.elamur.ai/free/en/papers/zmitrovich-2024-family-pretrained-transformer-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Dmitry Zmitrovich, Aleksandr Abramov, Andrey Kalmykov, et al.*2024 · 60 citations*
166. **[Puzzle Solving using Reasoning of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/giadikiaroglou-2024-puzzle-solving-reasoning-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Panagiotis Giadikiaroglou, Maria Lymperaiou, Giorgos Filandrianos, et al.*2024 · 48 citations*
167. **[ANLIzing the Adversarial Natural Language Inference Dataset](https://md.research.elamur.ai/free/en/papers/williams-2022-anlizing-adversarial-natural-language-inference/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Adina Williams, Tristan Thrush, Douwe Kiela*2022 · 48 citations*
168. **[Metaphor Understanding Challenge Dataset for LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-metaphor-understanding-challenge-dataset-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyu Tong, Rochelle Choenni, Martha Lewis, et al.*2024 · 47 citations*
169. [**Language models scale reliably with over-training and on downstream tasks arXiv:2403.08540**Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)
170. **[Fact Checking with Insufficient Evidence](https://md.research.elamur.ai/free/en/papers/atanasova-2022-fact-checking-insufficient-evidence/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2022 · 46 citations*
171. **[Polysemy–-Evidence from Linguistics, Behavioral Science, and Contextualized Language Models](https://md.research.elamur.ai/free/en/papers/haber-2024-polysemy-evidence-linguistics-behavioral-science/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Janosch Haber, Massimo Poesio*2024 · 44 citations*
172. **[Pragmatic competence of pre-trained language models through the lens of discourse connectives](https://md.research.elamur.ai/free/en/papers/pandia-2021-pragmatic-competence-pre-trained-language/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Lalchand Pandia, Yan Cong, Allyson Ettinger*2021 · 42 citations*
173. [**DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models arXiv:2507.09955**Luolin Xiong, Haofen Wang, Xi Chen, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2025-deepseek-paradigm-shifts-technical/)
174. **[MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks](https://md.research.elamur.ai/free/en/papers/nie-2023-moca-measuring-human-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Allen Nie, Yuhui Zhang, Atharva Amdekar, et al.*2023 · 41 citations*
175. **[A Few Topical Tweets are Enough for Effective User Stance Detection](https://md.research.elamur.ai/free/en/papers/samih-2021-few-topical-tweets-are-enough/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Younes Samih, Kareem Darwish*2021 · 40 citations*
176. [**DziriBERT: a Pre-trained Language Model for the Algerian Dialect arXiv:2109.12346**Amine Abdaoui, Mohamed Berrimi, Mourad Oussalah, et al.*2021 · 38 citations*](https://md.research.elamur.ai/free/en/papers/abdaoui-2021-dziribert-pre-trained-language-model/)
177. **[Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social Media](https://md.research.elamur.ai/free/en/papers/dong-2020-transformer-based-context-aware-sarcasm/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Xiangjue Dong, Changmao Li, Jinho D. Choi*2020 · 35 citations*
178. **[Probing Contextual Language Models for Common Ground with Visual Representations](https://md.research.elamur.ai/free/en/papers/ilharco-2021-probing-contextual-language-models-common/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Gabriel Ilharco, Rowan Zellers, Ali Farhadi, et al.*2021 · 33 citations*
179. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
180. **[Evaluating Document Coherence Modeling](https://md.research.elamur.ai/free/en/papers/shen-2021-evaluating-document-coherence-modeling/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aili Shen, Meladel Mistica, Bahar Salehi, et al.*2021 · 30 citations*
181. [**One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support arXiv:2306.09237**Ronja Stern, Vishvaksenan Rasiah, Veton Matoshi, et al.*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/stern-2023-one-law-many-languages-benchmarking/)
182. **[Sub-Character Tokenization for Chinese Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/si-2023-sub-character-tokenization-chinese-pretrained/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Chenglei Si, Zhengyan Zhang, Yingfa Chen, et al.*2023 · 29 citations*
183. **[Syntax Role for Neural Semantic Role Labeling](https://md.research.elamur.ai/free/en/papers/li-2021-syntax-role-neural-semantic-role/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Zuchao Li, Hai Zhao, Shexia He, et al.*2021 · 29 citations*
184. **[A Survey on Asking Clarification Questions Datasets in Conversational Systems](https://md.research.elamur.ai/free/en/papers/rahmani-2023-survey-asking-clarification-questions-datasets/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hossein A. Rahmani, Xi Wang, Yue Feng, et al.*2023 · 28 citations*
185. **[Evaluating ChatGPT and Bard AI on Arabic Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/thubaity-2023-evaluating-chatgpt-bard-ai-arabic/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Abdulmohsen Al-Thubaity, Sakhar Alkhereyf, Hanan Murayshid, et al.*2023 · 27 citations*
186. **[Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 27 citations*
187. [**Sentiment Analysis through LLM Negotiations arXiv:2311.01876**Xiaofei Sun, Xiaoya Li, Shengyu Zhang, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-sentiment-analysis-through-llm-negotiations/)
188. [**Scaling Latent Reasoning via Looped Language Models arXiv:2510.25741**Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-scaling-latent-reasoning-looped-language/)
189. [**ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding arXiv:2010.12148**Dongling Xiao, Yu-Kun Li, Han Zhang, et al.*2020 · 22 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2020-ernie-gram-pre-training/)
190. **[Arabizi Language Models for Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/baert-2020-arabizi-language-models-sentiment-analysis/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Gaétan Baert, Souhir Gahbiche, Guillaume Gadek, et al.*2020 · 21 citations*
191. **[Semantics of Multiword Expressions in Transformer-Based Models: A Survey](https://md.research.elamur.ai/free/en/papers/miletic-2024-semantics-multiword-expressions-transformer-based/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Filip Miletić, Sabine Schulte im Walde*2024 · 20 citations*
192. [**An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language Models arXiv:2301.09211**Saghar Hosseini, Hamid Palangi, Ahmed Hassan Awadallah*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2023-empirical-study-metrics-measure-representational/)
193. **[Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection](https://md.research.elamur.ai/free/en/papers/arakelyan-2023-topic-guided-sampling-data-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erik Arakelyan, Arnav Arora, Isabelle Augenstein*2023 · 19 citations*
194. [**A Survey on Automated Sarcasm Detection on Twitter arXiv:2202.02516**Bleau Moores, Vijay Mago*2022 · 19 citations*](https://md.research.elamur.ai/free/en/papers/moores-2022-survey-automated-sarcasm-detection-twitter/)
195. **[Improving Arabic Text Categorization Using Transformer Training Diversification](https://md.research.elamur.ai/free/en/papers/chowdhury-2020-improving-arabic-text-categorization-transformer/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Shammur Absar Chowdhury, Ahmed Abdelali, Kareem Darwish, et al.*2020 · 17 citations*
196. **[Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking](https://md.research.elamur.ai/free/en/papers/chen-2025-inner-thinking-transformer-leveraging-dynamic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilong Chen, Junyuan Shang, Zhenyu Zhang, et al.*2025 · 16 citations*
197. **[DiPlomat: A Dialogue Dataset for Situated Pragmatic Reasoning](https://md.research.elamur.ai/free/en/papers/li-2023-diplomat-dialogue-dataset-situated-pragmatic/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hengli Li, Song-Chun Zhu, Zilong Zheng*2023 · 15 citations*
198. **[When Truth Matters - Addressing Pragmatic Categories in Natural Language Inference (NLI) by Large Language Models (LLMs)](https://md.research.elamur.ai/free/en/papers/gubelmann-2023-when-truth-matters-addressing-pragmatic/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Reto Gubelmann, Aikaterini-lida Kalouli, Christina Niklaus, et al.*2023 · 15 citations*
199. [**SaudiBERT: A Large Language Model Pretrained on Saudi Dialect Corpora arXiv:2405.06239**Faisal Qarah*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/qarah-2024-saudibert-large-language-model-pretrained/)
200. **[New Arabic Medical Dataset for Diseases Classification](https://md.research.elamur.ai/free/en/papers/hammoud-2021-new-arabic-medical-dataset-diseases/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Jaafar Hammoud, Aleksandra Vatian, Natalia Dobrenko, et al.*2021 · 14 citations*

[← prev](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/) **2** [3](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/page/3/) [next →](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/cited-by/page/3/)

- [← back to](https://md.research.elamur.ai/free/en/papers/lan-2019-albert-lite-bert-self-supervised/) — ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
